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<div class="header">
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<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pub-attribs">Public 属性</a> &#124;
<a href="classpcl_1_1_regression_variance_node-members.html">所有成员列表</a>  </div>
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<div class="title">pcl::RegressionVarianceNode&lt; FeatureType, LabelType &gt; 模板类 参考</div>  </div>
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<p>Node for a regression trees which optimizes variance.  
 <a href="classpcl_1_1_regression_variance_node.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="regression__variance__stats__estimator_8h_source.html">regression_variance_stats_estimator.h</a>&gt;</code></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a0a97daa781ba92b787d65caf3c91c3ac"><td class="memItemLeft" align="right" valign="top"><a id="a0a97daa781ba92b787d65caf3c91c3ac"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a0a97daa781ba92b787d65caf3c91c3ac">RegressionVarianceNode</a> ()</td></tr>
<tr class="memdesc:a0a97daa781ba92b787d65caf3c91c3ac"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <br /></td></tr>
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<tr class="memitem:abaa10aed19a5efe2a0c836b1c4d0b0cb"><td class="memItemLeft" align="right" valign="top"><a id="abaa10aed19a5efe2a0c836b1c4d0b0cb"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#abaa10aed19a5efe2a0c836b1c4d0b0cb">~RegressionVarianceNode</a> ()</td></tr>
<tr class="memdesc:abaa10aed19a5efe2a0c836b1c4d0b0cb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:abaa10aed19a5efe2a0c836b1c4d0b0cb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a24c9f71bfad5c728bf605f445174ef17"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a24c9f71bfad5c728bf605f445174ef17">serialize</a> (std::ostream &amp;stream) const</td></tr>
<tr class="memdesc:a24c9f71bfad5c728bf605f445174ef17"><td class="mdescLeft">&#160;</td><td class="mdescRight">Serializes the node to the specified stream.  <a href="classpcl_1_1_regression_variance_node.html#a24c9f71bfad5c728bf605f445174ef17">更多...</a><br /></td></tr>
<tr class="separator:a24c9f71bfad5c728bf605f445174ef17"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3463081addd9c9e2237f764e031b6d4e"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a3463081addd9c9e2237f764e031b6d4e">deserialize</a> (std::istream &amp;stream)</td></tr>
<tr class="memdesc:a3463081addd9c9e2237f764e031b6d4e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Deserializes a node from the specified stream.  <a href="classpcl_1_1_regression_variance_node.html#a3463081addd9c9e2237f764e031b6d4e">更多...</a><br /></td></tr>
<tr class="separator:a3463081addd9c9e2237f764e031b6d4e"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
Public 属性</h2></td></tr>
<tr class="memitem:a4b1410ff0469bde2394b843c70229556"><td class="memItemLeft" align="right" valign="top"><a id="a4b1410ff0469bde2394b843c70229556"></a>
FeatureType&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a4b1410ff0469bde2394b843c70229556">feature</a></td></tr>
<tr class="memdesc:a4b1410ff0469bde2394b843c70229556"><td class="mdescLeft">&#160;</td><td class="mdescRight">The feature associated with the node. <br /></td></tr>
<tr class="separator:a4b1410ff0469bde2394b843c70229556"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a404fad6110f5fed14015839d59c6dca7"><td class="memItemLeft" align="right" valign="top"><a id="a404fad6110f5fed14015839d59c6dca7"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a404fad6110f5fed14015839d59c6dca7">threshold</a></td></tr>
<tr class="memdesc:a404fad6110f5fed14015839d59c6dca7"><td class="mdescLeft">&#160;</td><td class="mdescRight">The threshold applied on the feature response. <br /></td></tr>
<tr class="separator:a404fad6110f5fed14015839d59c6dca7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a52ce572a1d9852122bd74c074b76c2e3"><td class="memItemLeft" align="right" valign="top"><a id="a52ce572a1d9852122bd74c074b76c2e3"></a>
LabelType&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a52ce572a1d9852122bd74c074b76c2e3">value</a></td></tr>
<tr class="memdesc:a52ce572a1d9852122bd74c074b76c2e3"><td class="mdescLeft">&#160;</td><td class="mdescRight">The label value of this node. <br /></td></tr>
<tr class="separator:a52ce572a1d9852122bd74c074b76c2e3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a266146f39a982a8f1c1f167c29e1b63d"><td class="memItemLeft" align="right" valign="top"><a id="a266146f39a982a8f1c1f167c29e1b63d"></a>
LabelType&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a266146f39a982a8f1c1f167c29e1b63d">variance</a></td></tr>
<tr class="memdesc:a266146f39a982a8f1c1f167c29e1b63d"><td class="mdescLeft">&#160;</td><td class="mdescRight">The variance of the labels that ended up at this node during training. <br /></td></tr>
<tr class="separator:a266146f39a982a8f1c1f167c29e1b63d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a84b352820a9f306fd303f5fca7792da0"><td class="memItemLeft" align="right" valign="top"><a id="a84b352820a9f306fd303f5fca7792da0"></a>
std::vector&lt; <a class="el" href="classpcl_1_1_regression_variance_node.html">RegressionVarianceNode</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_regression_variance_node.html#a84b352820a9f306fd303f5fca7792da0">sub_nodes</a></td></tr>
<tr class="memdesc:a84b352820a9f306fd303f5fca7792da0"><td class="mdescLeft">&#160;</td><td class="mdescRight">The child nodes. <br /></td></tr>
<tr class="separator:a84b352820a9f306fd303f5fca7792da0"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;class FeatureType, class LabelType&gt;<br />
class pcl::RegressionVarianceNode&lt; FeatureType, LabelType &gt;</h3>

<p>Node for a regression trees which optimizes variance. </p>
</div><h2 class="groupheader">成员函数说明</h2>
<a id="a3463081addd9c9e2237f764e031b6d4e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3463081addd9c9e2237f764e031b6d4e">&#9670;&nbsp;</a></span>deserialize()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;class FeatureType , class LabelType &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_node.html">pcl::RegressionVarianceNode</a>&lt; FeatureType, LabelType &gt;::deserialize </td>
          <td>(</td>
          <td class="paramtype">std::istream &amp;&#160;</td>
          <td class="paramname"><em>stream</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
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</div><div class="memdoc">

<p>Deserializes a node from the specified stream. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">stream</td><td>The source for the deserialization. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;      {</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        <a class="code" href="classpcl_1_1_regression_variance_node.html#a4b1410ff0469bde2394b843c70229556">feature</a>.deserialize (stream);</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160; </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        stream.read (<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;<a class="code" href="classpcl_1_1_regression_variance_node.html#a404fad6110f5fed14015839d59c6dca7">threshold</a>), <span class="keyword">sizeof</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a404fad6110f5fed14015839d59c6dca7">threshold</a>));</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;        stream.read (<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;<a class="code" href="classpcl_1_1_regression_variance_node.html#a52ce572a1d9852122bd74c074b76c2e3">value</a>), <span class="keyword">sizeof</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a52ce572a1d9852122bd74c074b76c2e3">value</a>));</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        stream.read (<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;<a class="code" href="classpcl_1_1_regression_variance_node.html#a266146f39a982a8f1c1f167c29e1b63d">variance</a>), <span class="keyword">sizeof</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a266146f39a982a8f1c1f167c29e1b63d">variance</a>));</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        <span class="keywordtype">int</span> num_of_sub_nodes;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        stream.read (<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;num_of_sub_nodes), <span class="keyword">sizeof</span> (num_of_sub_nodes));</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        <a class="code" href="classpcl_1_1_regression_variance_node.html#a84b352820a9f306fd303f5fca7792da0">sub_nodes</a>.resize (num_of_sub_nodes);</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        <span class="keywordflow">if</span> (num_of_sub_nodes &gt; 0)</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        {</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> sub_node_index = 0; sub_node_index &lt; num_of_sub_nodes; ++sub_node_index)</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;          {</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;            <a class="code" href="classpcl_1_1_regression_variance_node.html#a84b352820a9f306fd303f5fca7792da0">sub_nodes</a>[sub_node_index].deserialize (stream);</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;          }</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        }</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;      }</div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_node_html_a266146f39a982a8f1c1f167c29e1b63d"><div class="ttname"><a href="classpcl_1_1_regression_variance_node.html#a266146f39a982a8f1c1f167c29e1b63d">pcl::RegressionVarianceNode::variance</a></div><div class="ttdeci">LabelType variance</div><div class="ttdoc">The variance of the labels that ended up at this node during training.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:117</div></div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_node_html_a404fad6110f5fed14015839d59c6dca7"><div class="ttname"><a href="classpcl_1_1_regression_variance_node.html#a404fad6110f5fed14015839d59c6dca7">pcl::RegressionVarianceNode::threshold</a></div><div class="ttdeci">float threshold</div><div class="ttdoc">The threshold applied on the feature response.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:112</div></div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_node_html_a4b1410ff0469bde2394b843c70229556"><div class="ttname"><a href="classpcl_1_1_regression_variance_node.html#a4b1410ff0469bde2394b843c70229556">pcl::RegressionVarianceNode::feature</a></div><div class="ttdeci">FeatureType feature</div><div class="ttdoc">The feature associated with the node.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:110</div></div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_node_html_a52ce572a1d9852122bd74c074b76c2e3"><div class="ttname"><a href="classpcl_1_1_regression_variance_node.html#a52ce572a1d9852122bd74c074b76c2e3">pcl::RegressionVarianceNode::value</a></div><div class="ttdeci">LabelType value</div><div class="ttdoc">The label value of this node.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:115</div></div>
<div class="ttc" id="aclasspcl_1_1_regression_variance_node_html_a84b352820a9f306fd303f5fca7792da0"><div class="ttname"><a href="classpcl_1_1_regression_variance_node.html#a84b352820a9f306fd303f5fca7792da0">pcl::RegressionVarianceNode::sub_nodes</a></div><div class="ttdeci">std::vector&lt; RegressionVarianceNode &gt; sub_nodes</div><div class="ttdoc">The child nodes.</div><div class="ttdef"><b>Definition:</b> regression_variance_stats_estimator.h:120</div></div>
</div><!-- fragment -->
</div>
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<a id="a24c9f71bfad5c728bf605f445174ef17"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a24c9f71bfad5c728bf605f445174ef17">&#9670;&nbsp;</a></span>serialize()</h2>

<div class="memitem">
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<div class="memtemplate">
template&lt;class FeatureType , class LabelType &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1_regression_variance_node.html">pcl::RegressionVarianceNode</a>&lt; FeatureType, LabelType &gt;::serialize </td>
          <td>(</td>
          <td class="paramtype">std::ostream &amp;&#160;</td>
          <td class="paramname"><em>stream</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Serializes the node to the specified stream. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">stream</td><td>The destination for the serialization. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;      {</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        <a class="code" href="classpcl_1_1_regression_variance_node.html#a4b1410ff0469bde2394b843c70229556">feature</a>.serialize (stream);</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160; </div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        stream.write (<span class="keyword">reinterpret_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;<a class="code" href="classpcl_1_1_regression_variance_node.html#a404fad6110f5fed14015839d59c6dca7">threshold</a>), <span class="keyword">sizeof</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a404fad6110f5fed14015839d59c6dca7">threshold</a>));</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160; </div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        stream.write (<span class="keyword">reinterpret_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;<a class="code" href="classpcl_1_1_regression_variance_node.html#a52ce572a1d9852122bd74c074b76c2e3">value</a>), <span class="keyword">sizeof</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a52ce572a1d9852122bd74c074b76c2e3">value</a>));</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        stream.write (<span class="keyword">reinterpret_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;<a class="code" href="classpcl_1_1_regression_variance_node.html#a266146f39a982a8f1c1f167c29e1b63d">variance</a>), <span class="keyword">sizeof</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a266146f39a982a8f1c1f167c29e1b63d">variance</a>));</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160; </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">int</span> num_of_sub_nodes = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (<a class="code" href="classpcl_1_1_regression_variance_node.html#a84b352820a9f306fd303f5fca7792da0">sub_nodes</a>.size ());</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        stream.write (<span class="keyword">reinterpret_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">char</span>*<span class="keyword">&gt;</span> (&amp;num_of_sub_nodes), <span class="keyword">sizeof</span> (num_of_sub_nodes));</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> sub_node_index = 0; sub_node_index &lt; num_of_sub_nodes; ++sub_node_index)</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        {</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;          <a class="code" href="classpcl_1_1_regression_variance_node.html#a84b352820a9f306fd303f5fca7792da0">sub_nodes</a>[sub_node_index].serialize (stream);        </div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        }</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;      }</div>
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